37 citations · 105 across the 4 of their papers we have counts for
4 papers
Multiple-bias sensitivity analysis using bounds
Louisa H. Smith, Maya B. Mathur, Tyler J. VanderWeele
Unmeasured confounding, selection bias, and measurement error are well-known sources of bias in epidemiologic research. Methods for assessing these biases have their own limitation…
How to apply multiple imputation in propensity score matching with partially observed confounders: a simulation study and practical recommendations
Albee Y. Ling, Maria E. Montez-Rath, Maya B. Mathur +2
Propensity score matching (PSM) has been widely used to mitigate confounding in observational studies, although complications arise when the covariates used to estimate the PS are…
Outcome-wide longitudinal designs for causal inference: a new template for empirical studies
Tyler J. VanderWeele, Maya B. Mathur, Ying Chen
In this paper we propose a new template for empirical studies intended to assess causal effects: the outcome-wide longitudinal design. The approach is an extension of what is often…
Simulating realistically complex comparative effectiveness studies with time-varying covariates and right-censored outcomes
Maria E. Montez-Rath, Kristopher Kapphahn, Maya B. Mathur +3
Simulation studies are useful for evaluating and developing statistical methods for the analyses of complex problems. Performance of methods may be affected by multiple complexitie…